Minimum superlattice thermal conductivity from molecular dynamics

The dependence of superlattice thermal conductivity on period length is investigated by molecular dynamics simulation. For perfectly lattice matched superlattices, a minimum is observed when the period length is of the order of the effective phonon mean free path. As temperature decreases and interatomic potential strength increases, the position of the minimum shifts to larger period lengths. The depth of the minimum is strongly enhanced as mass and interatomic potential ratios of the constituent materials increase. The simulation results are consistent with phonon transmission coefficient calculations, which indicate increased stop bandwidth and thus strongly enhanced Bragg scattering for the same conditions under which strong reductions in thermal conductivity are found. When nonideal interfaces are created by introducing a 4% lattice mismatch, the minimum disappears and thermal conductivity increases monotonically with period length. This result may explain why minimum thermal conductivity has not been observed in a large number of experimental studies

CA2: Class-Agnostic Adaptive Feature Adaptation for One-class Classification

One-class classification (OCC), i.e., identifying whether an example belongs to the same distribution as the training data, is essential for deploying machine learning models in the real world. Adapting the pre-trained features on the target dataset has proven to be a promising paradigm for improving OCC performance. Existing methods are constrained by assumptions about the number of classes. This contradicts the real scenario where the number of classes is unknown. In this work, we propose a simple class-agnostic adaptive feature adaptation method (CA2). We generalize the center-based method to unknown classes and optimize this objective based on the prior existing in the pre-trained network, i.e., pre-trained features that belong to the same class are adjacent. CA2 is validated to consistently improve OCC performance across a spectrum of training data classes, spanning from 1 to 1024, outperforming current state-of-the-art methods. Code is available at https://github.com/zhangzilongc/CA2.Comment: Submit to AAAI 202

Thermal expansion and impurity effects on lattice thermal conductivity of solid argon

Thermal expansion and impurity effects on the lattice thermal conductivity of solid argon have been investigated with equilibrium molecular dynamics simulation. Thermal conductivity is simulated over the temperature range of 20 – 80 K. Thermal expansion effects, which strongly reduce thermal conductivity, are incorporated into the simulations using experimentally measured lattice constants of solid argon at different temperatures. It is found that the experimentally measured deviations from a T-1 high-temperature dependence in thermal conductivity can be quantitatively attributed to thermal expansion effects. Phonon scattering on defects also contributes to the deviations. Comparison of simulation results on argon lattices with vacancy and impurity defects to those predicted from the theoretical models of Klemens and Ashegi et al. demonstrates that phonon scattering on impurities due to lattice strain is stronger than that due to differences in mass between the defect and the surrounding matrix. In addition, the results indicate the utility of molecular dynamics simulation for determining parameters in theoretical impurity scattering models under a wide range of conditions. It is also confirmed from the simulation results that thermal conductivity is not sensitive to the impurity concentration at high temperatures

Sequence Dependent Repair of 1,N6-Ethenoadenine by DNA Repair Enzymes ALKBH2, ALKBH3, and AlkB

Mutation patterns of DNA adducts, such as mutational spectra and signatures, are useful tools for diagnostic and prognostic purposes. Mutational spectra of carcinogens derive from three sources: adduct formation, replication bypass, and repair. Here, we consider the repair aspect of 1,N6-ethenoadenine (εA) by the 2-oxoglutarate/Fe(II)-dependent AlkB family enzymes. Specifically, we investigated εA repair across 16 possible sequence contexts (5′/3′ flanking base to εA varied as G/A/T/C). The results revealed that repair efficiency is altered according to sequence, enzyme, and strand context (ss- versus ds-DNA). The methods can be used to study other aspects of mutational spectra or other pathways of repair